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SQLite is widely used in mobile, desktop, and edge applications but has no production-ready Change Data Capture connector. This project builds a Debezium source connector for SQLite that captures row-level changes by directly parsing the SQLite Write-Ahead Log (WAL) binary file by decoding B-tree leaf pages, diffing old and new page states, and producing standard Debezium change events with correct before and after values, without any application modifications. Deliverables include a deployable Kafka Connect plugin with full WAL binary parsing, initial snapshot, streaming with safe checkpoint lifecycle management, transaction metadata support, and a complete test suite with documentation.

<p>This proposal is about developing Fretboard: an A/B testing framework for Android written in Kotlin, taking as foundation the Switchboard fork used in Firefox for Android.</p> <p>The goal is to make a reusable library decoupled from both the client and server storage mechanism which will allow to make A/B tests on Android apps: check if a user is part of an experiment, schedule frequent updates, get experiment associated metadata, as well as force specific experiments value in order to test the app, for example.</p> <p>It will also allow security features: certificate pinning and experiment collection signature verification. The library will be deployed to jcenter and also integrated into Firefox Focus.</p>

At current state of the product, listens on ListenBrainz are collected in the UTC instead of their local timestamp, without taking DST in to consideration. Adding timezone preference for users and adding the time zone field in submitted listens will contribute to the analysis and thus provide better user experience. This project aims to add users’ timezone preference paired with their submitted listens. The main work involves making an appropriate table in Postgres to store timezones, designing a react UI page and implementing the corresponding API endpoints. The stretch goal is to include local timestamp in the API, and extract the timezone information from that timestamp to store in the database. The expected outcome is a finished feature ready to be merged into production code.

<p>A crucial component of the openSNP infrastructure is to make the available data more accessible to the general users and scientists alike. Currently, the portal has independent listing of user <em>Phenotypes</em> and parsed <em>SNP</em>s. Each <em>SNP</em>s entry have an additional information section where data from other credible sources (PLoS, Mendeley, Genome.gov) is made available. There is, however, no direct or inferred relationship available between the <em>SNP</em>s and the corresponding <em>Phenotypes</em> (as reported). <strong>This project proposes to bridge the connectivity between existing <em>Phenotypes</em> and genetic variants with the help of already mined data and implementing additional services as necessary.</strong></p>

The project enhances Plone 6 by integrating Really Simple Syndication (RSS) support through two key components: exposing Plone content as RSS feeds and embedding external RSS feeds within Plone. A new rss_feed content type with a listing block, provided by the backend rss-provider add-on, and the express middleware in volto-rss-provider enable users to share Plone content as RSS feeds. The volto-rss-receiver add-on, which relies on the rss_mixer_data endpoint from the rss-receiver backend, supports efficient retrieval and display of external RSS feeds within Plone. This project simplifies content syndication and broadens the reach of Plone content, enhancing user engagement and accessibility.

<p>“Pontoon is Mozilla's localization tool, used by hundreds of contributors to translate Firefox, mozilla.org, and many other Mozilla products. It is critical to shipping Firefox to as many users as possible, all around the world.”</p> <p>Since active user participation and onboarding is one of the key components for the achievement of Pontoon’s goal towards localization, the idea is to improve the experience of first-time users of Pontoon by defining a "path to first contribution" explaining the basic flow and ins and out of contributing towards localising Mozilla applications by adding a guided interactive tour, a walkthrough for explaining basic functionality for unauthenticated user and a better “Learn More” link replacing the current gitbook link and making all of these as smooth as possible.</p>

<p>Firefox for Android is one of the most widely used browsers. The team is currently involved in reducing the size of the Android Package - APK. As a first step of this ongoing effort the fonts are excluded from being packaged along with the APK. The scope of reducing the size of the APK does not stop there. There are various opportunities and scopes for further reducing the size of APK such as excluding hyphenation dictionaries, translation and so on from being packaged. The task is to download the excluded assets from the server. This initiative can effectively reduce the size of the APK File.I propose to implement features that enables the browser to download the assets like hyphenation dictionaries at the runtime.I also propose to implement a helper class which can be used to smartly schedule the downloads based on the conditions and smartly reschedule the failed downloads and exclude other assets like localization files.</p>

The project proposal is to bring password-less authentication to Plone 6 by implementing WebAuthn, a password-less web standard by W3C. The proposal suggests that the implementation should allow the user to decide whether to use WebAuthn as the primary or second-factor authenticator. WebAuthn uses public key cryptography to store user credentials, which makes it more secure than traditional password-based authentication methods. However, the proposal also discusses the challenges of using WebAuthn, such as the Scenario where the authenticator device is not available or lost. The proposed solutions include backup codes, recovery codes, and administrator reset, but all of them require storing some kind of secret on the server, which is a security concern. The proposal suggests alternative solutions like encouraging users to use at least two different Authenticating devices to register.

<p>With the number of sequenced and annotated genomes continuously increasing, there is a need for new algorithms and tools for comparative analyses both at the nucleotide and genic levels. The Genome Context Viewer (GCV) is an OSS tool that enables comparative genomics by using gene families as a unit of search and comparison. It currently uses Chado as a reference implementation for its data services and can be integrated with other GMOD components via a service layer/API. This work will create an extension module that will integrate new and existing pan-genomics algorithms into GCV while leveraging the existing UI for visualization purposes. This will help to serve communities facing the challenges of having multiple reference genomes within a single species, as well as improving GCV’s utility for clade-oriented resources.</p>

This project aims to extend the existing cBioAbstractor prototype into a schema-driven formatting pipeline that assists curators in transforming heterogeneous supplemental datasets into cBioPortal-compatible formats. Currently, curation is a manual and time-consuming process due to inconsistent file structures, lack of automated schema mapping, and the need to interpret validation errors manually. This results in inefficiencies, variability, and high onboarding effort. My preliminary extension implementation suggests the feasibility of this approach by connecting existing components, introducing fuzzy column normalization, and providing a simple interface for file upload, transformation, and result inspection. Initial qualitative experiments show that the system can reconstruct correct cBioPortal formats from intentionally perturbed datasets, suggesting strong potential for reducing manual work and improving consistency.

Karmada would like to improve the UT coverage of the code to better maintain the quality of the code and reduce the introduction of defects. Increase the UT coverage rate to 50% to 60% (currently, the UT coverage rate is [28.26%](https://app.codecov.io/gh/karmada-io/karmada) ). The entire Karmada repository is a bit large for one project, so we will split it into two projects. The current focus is mainly on `karmada-search`, `karmada-operator`, `karmada-webhook` components. Expected Outcome: - Increase the UT (Unit Test) coverage by more than 25% and add more than 5500 lines of code coverage except for the following directories: pkg/controllers pkg/dependenciesdistributor pkg/descheduler pkg/detector pkg/estimator pkg/scheduler pkg/resourceinterpreter pkg/util

Discovering new music can be quite an adventure and may lead to finding music which you will hear on repeat for a long time. Currently, ListenBrainz offers many ways to do it, like Fresh Releases, Hue sound, Similar Users and many more. Another powerful discovery tool which can be added to suite is an Artist Similarity Graph. It will provide an intuitive way for the users to analyze relationships between artists. In this way, the users can get exposure to new artists with a music style similar to their favorite artists. This project aims to provide a pleasant UX for the same, while delivering the following features in the UI: 1. Display a graph of related artists. 2. Link to artist's MusicBrainz profile. 3. Play artist's most popular album. 4. Play the most popular recording.

One of the goals of this project is to utilize Deep Learning models to better interpret underwater sounds. We are required to train neural networks streams of audio data to separate marine mammal vocalization sounds (orcas and humpback whales) from other background noise like that of ships and other vessels. Next, we have to train two different neural networks- one for classifying the whale vocalization sounds and the other one to classify ship noises. The second part of the project involves building an efficient vessel monitoring system. We will use AIS data to detect and track larger commercial vessel and some private yachts. The non-AIS boats can be tracked using RADAR and camera data using Marine Monitoring system. Once we are done training all the models, we can deploy the detectors on the cloud and on the Jetson Nano.

<p>WildFly Elytron is a new security framework developed by WildFly to provide a single unified security framework across whole of the application server which replaced the pre existing Java Authentication and Authorization Service (JAAS) which used to be the standard Pluggable Authentication Module (PAM) information security framework. To extend Elytron’s functionality beyond the existing security realms, custom security realms can be implemented using existing Elytron’s APIs and SPIs for their usage in WildFly Elytron subsystem. Now to extend this functionality of custom development to scripting languages other than Java, Java ScriptEngine is used. During the summer as the project of GSoC under JBoss Community, I’ll be working on extending the functionality of WildFly Elytron’s implementation of custom security realms using other scripting languages.</p>

Currently, keeping privacy in mind, Matrix uses seshat to store a searchable database on the user’s device itself. As the number of conversations and messages increase, maintaining an index on the client side becomes tougher. The solution to these problems is a Searchable Symmetric Encryption (SSE) scheme that lets the client safely store an encrypted database on an untrusted server and search through it with full privacy. This project will implement, in particular, the keyword search scheme outlined in a Demertzis et al. paper titled “Fast Searchable Encryption with Tunable Locality”. I will achieve this by creating a Python library that exposes methods to create, update and search on encrypted indices stored in content repositories in a Matrix homeserver. As a part of the project I will be demonstratively integrating the library into an existing Matrix client. Additionally, I will submit results of preliminary performance evaluation.

<p>The main goal of this project is to implement a mechanism to be in sync with the latest human data submitted to dbSNP. Once imported, this information can be distributed via EVA implementations of the GA4GH APIs htsget and Beacon specifications, as well as the EVA website.</p> <h6>Acceptance criteria</h6> <p>Given a dbSNP FTP directory with the human variant information, the pipeline should parse JSONs for each chromosome and write the variants from the JSONs to the EVA archive</p> <h6>Needed tasks</h6> <ul> <li>Construct an object model for dbSNP and parse the JSONs to objects in that model</li> <li>Convert the objects in the dbSNP model to the EVA variant object model</li> <li>Construct a variant object by including its component objects from above. Use the Variant writer of variation-commons to write the variants to the EVA archive</li> </ul>

This project aims to seamlessly integrate all functionalities of the ListenBrainz website's Dashboard into the ListenBrainz iOS app. This integration will enable users not only to view their own dashboard within the app but also to explore the dashboards of other users. This exploration will be implemented using various navigation techniques and state management. Also, this project aims to revamp the feed section of the app and to maintain design consistency with the ListenBrainz website. The dashboard offers a variety of features such as detailed music listening statistics, recent listens, taste, and more, all within a user-friendly and engaging mobile interface. In the implementation, the SwiftUI framework will be utilized to craft an intuitive and visually appealing user interface while Apple's Combine framework will handle asynchronous event management. Additionally, Alamofire library will be employed for networking tasks, ensuring smooth communication between the app and the backend server.

<p>Elytron is an open-source, standalone library made with the purpose to provide a single, unified security solution across the whole Wildfly application server, which earlier was using two separate security solutions, one based on JAAS for application and other based on SASL for management. While developing Elytron the idea was to provide a better and stronger authentication and build something that does more than just unifying the security solution. Intrusion Detection using Elytron is aimed at doing the same i.e. to extend Elytron’s functionality. Intrusion Detection is the art of sensing when a system or network is being used inappropriately or without authorization. Without intrusion detection, an attacker can attempt attacks many times until an attack is finally successful. Intrusion detection allows for these attacks to be identified before a successful attack is likely to occur. The purpose of this project is to implement an Intrusion Detection system that detects suspicious activity or a potential attack and report it to the administrator.</p>

<p>Drools and Java can work together. Java and Minecraft work together. The obvious next step is to get Drools and Minecraft to work together.</p> <p>The plan is as follows:</p> <p>--A Minecraft mod boots up a list of Drools rules. These are either stored in a predetermined directory, or listed in a config file.</p> <p>--Minecraft does it's start-up routines. The user loads a world.</p> <p>--Each tick (world update) (or X ticks, determined by efficiency needs), the mod executes the rules.</p> <p>--The rules call functions in the mod's Drools API. This is where the majority of the work will come in—I'll have to write a largish set of functions for drools to use. The functions will take two shapes: returning boolean values for tests, or acting upon the world.</p> <p>--The mod reacts to the function calls, altering the world...</p> <p>–...which the user then interacts with.</p>

Modern AI systems relying on Retrieval-Augmented Generation (RAG) often suffer from stale data due to batch-based updates. This project, PyDebeziumAI, aims to solve this by enabling real-time synchronization between databases and LLM pipelines using Debezium Change Data Capture (CDC). The project will extend pydbzengine to stream CDC events directly into LangChain and LangGraph by transforming database changes into semantic Document objects and updating vector stores in real time. Key deliverables include: - A Python library integrating Debezium with LangChain/LangGraph - Real-time vector store synchronization (Chroma, PGVector, Milvus) - Pluggable document transformation and ID strategies - End-to-end examples (RAG chatbot, reactive agent, dashboard) - Full documentation, testing, and PyPI release This will provide a production-ready bridge between CDC systems and AI frameworks, ensuring always up-to-date LLM context.

<p>In the last GSoC, kingiw created an initial version of casbin.js. This version has a CASL-like API. He also adds support to go-casbin and node-casbin.</p> <p>However, casbin.js relies on an insufficient way to share permissions between the frontend and backend. The backend needs to send the whole policy definition model to the frontend, which will use node-casbin to check the permission. This method requires a heavy data transfer in between, and has potential security problems.</p> <p>To build a production-ready frontend permission control library, we need to</p> <ul> <li>Design a new data structure to only store one-user permission.</li> <li>Add a full set of API to operate on the data structure.</li> <li>Implement integration with the frontend frameworks like React or Vue.js.</li> <li>Add util function in different implementations of Casbin.</li> </ul>

This project integrates n8n, a no-code workflow automation platform, with OpenVINO Model Server to let users build AI-powered workflows that run on Intel GPUs and NPUs. The core is a custom n8n node package that connects to OVMS - users pick a model, choose a target device, and the node handles inference. The system is deployed through Podman Compose with one command. The primary workflow is a Smart Document Processing Pipeline: it watches a folder for incoming documents, runs text extraction on NPU, classifies and extracts entities using an LLM on GPU, and saves results locally. OpenVINO's AUTO plugin handles device selection automatically based on availability and load. Deliverables: custom n8n node package with GPU/NPU/AUTO device selection, Podman Compose deployment, the document processing pipeline, 2-3 additional workflow templates (RAG chatbot, multimodal content analysis), and documentation with installation guide and tutorials."

<p>MusicBrainz has client libraries for various programming languages such as C++, Python, Java, Go and more. However, we're still missing out on a proper client library for the Rust programming language. There previously have been attempts on creating such a client library, such as the <a href="https://github.com/leoschwarz/musicbrainz_rust" target="_blank"><code>musicbrainz_rust</code></a> (not being maintained at the moment) and the <a href="https://github.com/oknozor/musicbrainz_rs" target="_blank"><code>musicbrainz_rs</code></a> projects, but none of these attempts entirely wrap around the MusicBrainz Web-API.</p> <p>As a part of GSoC'21, I propose to implement further functionality in <code>musicbrainz_rs</code>, a Rust client library which has proper automated tests and has been carefully documented along with examples. However, it still misses out on covering some important functionality from the Web-API, namely the Search feature and the CoverArt endpoint. There are also further possible improvements that could be made, such as gracefully handling rate-limiting from the MusicBrainz servers by performing auto-retries on failed queries in the library.</p>